降低快速搜索算法中局部最优误差的研究
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摘要
运动估计是视频编码器的重要组成部分,占整个压缩编码50%以上的计算量。而块匹配搜索又是运动估计的核心,全局搜索算法由于运算复杂度较大,没有实用价值,为了降低搜索量,科研人员提出了各种快速搜索算法,如:三步法、四步法、钻石法等。
     快速搜索算法虽然能够有效的降低搜索量,由于它是对搜索窗有选择的搜索,容易陷入局部最优产生误差,称为局部最优误差,如何解决局部最优问题一直是研究的热点。通过分析,降低局部最优误差的方法一般分为两类:一类是改进搜索算法,另一类是改进搜索方案,本文就是基于这两类方法展开讨论。
     在对经典快速搜索算法分析的基础上,本文提出了一种改进的快速搜索算法——两阶段搜索算法,主要通过提高第一步的搜索量来达到降低局部最优误差的目的。
     但如何评价一个快速搜索算法的好坏是提出新算法时要面临的问题。由于相对快速搜索算法而言,全局搜索算法具有搜索量最大、搜索精度最高的特征,本文提出把全局搜索算法作为一个参考点,所有待评价的快速搜索算法都与这个参考点进行比较,得出一个量值,该量值就作为快速搜索算法质量值,通过比较质量值来达到比较快速搜索算法的目的。
     多分辨率运动估计是一种搜索方案的改进,它不再仅局限于对相邻帧原图进行搜索,而是通过选择初始搜索点的方法来降低快速搜索算法的局部最优误差。小波域多分辨率运动估计就是在这个基础上发展起来的,它利用小波变换良好的多尺度特性,得到不同分辨率的子图,构造出多分辨率塔型结构。本文通过实验分析得出:相对空间域搜索而言,基于小波域多分辨率运动估计的快速搜索算法确实能够降低快速搜索算法局部最优误差,但增加了搜索层数,在一定程度上增加了运动估计的复杂度。为解决这个问题本文提出了基于小波域的越级多分辨率运动估计思想,并结合快速搜索算法,在降低局部最优误差的前提下,有效的降低运算复杂度。
Motion Estimation plays a very important part in video encoder, which accounted for more than 50% of the amount of coding. Because of computational complexity of exhaustive search, it has no practical value. In order to reduce the amount of computation, the researchers put forward a variety of fast search algorithms such as three step search, four step search, diamond search, etc.
    Although fast search algorithms can effectively reduce the amount of search, because of their choice to search in the search window, it can easily fall into local optimal and thus produce error, which is called as local optimal error. How to solve local optimal problem has always been a hot topic. Through analysis, the approach to reduce the local optimal error can generally be divided into two types: one is to improve the search algorithm, the other is to improve search plan, and this paper is to further the discussion on the base of the two methods.
    On the basis of the analysis of the classical fast search algorithms, this paper proposes a modified fast search algorithm, two-phase search algorithm. It mainly adopts improving the first step search volume to achieve the purpose of reducing local optimal error.
    But how to assess the quality of a fast search algorithm is the problem faced when proposes a new algorithm. In comparison to fast search algorithms, the exhaustive search algorithm has the features of the largest and highest accuracy of search, so this paper proposed exhaustive search algorithm as a reference point. All fast search algorithms for the evaluation compare with the reference point, and get a value. The value is as the quality value of a fast search algorithm.
    Multi-resolution motion estimation is an improvement to the search plan, and it no longer limited to the search of two adjacent frames, but by choosing initial search point to reduce the local optimal error of the fast search algorithms. The wavelet-based multi-resolution motion estimation is developed on this basis. It uses multi-scale feature of the wavelet to get sub-images which own different resolution, and then constructs the pyramid structure of multi-resolution. In comparison to relative fast search algorithms
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